Analyze/diagnose/debug/troubleshoot why an AWX job failed and get actionable fix suggestions. Use this when user asks
AI agents call awx_job_failure_summary to retrieve information from Pypi:awx without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool retrieves and analyzes existing job failure data to provide diagnostic insights. It does not create, modify, delete, execute code, or commit financial transactions. It is purely informational—reading job failure logs/state and returning analysis. The low severity reflects that misuse would only expose existing information about failed jobs, not cause operational impact.
From the tool's definition Tool description states: 'Analyze/diagnose/debug/troubleshoot why an AWX job failed and get actionable fix suggestions.' The verbs (analyze, diagnose, debug, troubleshoot) and the stated purpose of retrieving failure information and suggestions indicate data…
Documented attack patterns abuse exactly the kind of access awx_job_failure_summary gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Pypi:awx, and nothing reaches the server without passing your rules. This is the rule we recommend for awx_job_failure_summary:
{
"version": "1",
"default": "deny",
"tools": {
"awx_job_failure_summary": {}
}
} awx_job_failure_summary is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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Analyze/diagnose/debug/troubleshoot why an AWX job failed and get actionable fix suggestions. Use this when user asks. It is categorised as a Read tool in the Pypi:awx MCP Server, which means it retrieves data without modifying state.
Register the Pypi:awx MCP server in PolicyLayer and add a rule for awx_job_failure_summary: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Pypi:awx. Nothing to install.
awx_job_failure_summary is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the awx_job_failure_summary rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for awx_job_failure_summary. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
awx_job_failure_summary is provided by the Pypi:awx MCP server (SurgeX-Labs/awx-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Pypi:awx, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
Free to start. No card required.
50 Pypi:awx tools catalogued and risk-classified — across an index of 43,000+ MCP servers.